Senior Software Engineer

🕒 Junho 23

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Horizon3.ai

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2019

🔒 Cibersegurança

🤖 Inteligência Artificial

☁️ SaaS

Cybersecurity • Artificial Intelligence • SaaS

A plataforma NodeZero™ capacita sua organização a continuamente encontrar, corrigir e verificar sua superfície de ataque explorável. Reduza seu risco de segurança ao encontrar autonomamente fraquezas em sua rede, sabendo como priorizá-las e corrigi-las, e verificando imediatamente se suas correções funcionam. O NodeZero oferece pentests autônomos seguros para produção e outras operações de avaliação chave que escalam através de seus maiores ambientes internos, externos, em nuvem e em nuvem híbrida. Sem necessidade de agentes, sem código para escrever e sem consultores para contratar. Somos uma fusão de ex-operadores cibernéticos das Operações Especiais dos EUA, engenheiros de startups e praticantes de cibersegurança anteriormente frustrados. Estamos comprometidos em ajudar a resolver nossos problemas comuns de segurança: ferramentas de segurança ineficazes, falsos positivos resultando em fadiga de alerta, pontos cegos, cultura de segurança "para cumprir tabela", escassez de habilidades em cibersegurança e o longo tempo e custo de contratar consultores externos.

Descrição

• Build and evolve the agent harness and orchestration that turns an LLM into a reliable autonomous pentester, the loop that reasons over an application, forms attack hypotheses, acts, and verifies results. • Design the tools and tool-shaped feedback the agent uses to probe and exploit, and the structured-output and validation layers that keep it reliable (e.g., hook-enforced mandatory validation, schema-constrained outputs). • Translate the team's offensive expertise into repeatable agent capabilities — partnering directly with our attackers to encode how they think into something the agent can do consistently. • Own and grow our evaluation infrastructure: benchmark suites, a failure-mode taxonomy across the pipeline (discovery → hypothesis → exploitation → verification), and regression detection, so we actually know whether the agent is getting better. • Manage LLM inference in production: model selection, prompt and context engineering, and keeping cost and latency under control (we run on AWS Bedrock with centralized cost tracking). • Hold the line on production-safety and no-false-positives, every finding the agent reports has to be real and reproducible.

🎯 Requisitos

• 5+ years building production software, with strong Python. • Hands-on experience building LLM-powered applications or agents, tool use / function calling, structured outputs, multi-step orchestration, and the glue that makes it all hold together. • A track record of making LLMs reliable in production, you've wrestled nondeterminism, designed around model limitations, and shipped something that worked when it mattered. • Real experience with evaluation: you've built or owned the harness that tells you whether a model or agent change is an improvement, not just a vibe. • Strong instincts for prompt and context engineering, and the judgment to keep the model's job small and well-scoped. • Solid software fundamentals — testing, observability, and the discipline to keep a complex agent debuggable. • Ownership mentality, comfortable owning a critical, fast-moving subsystem end to end.

🏖️ Benefícios

• Health, vision & dental insurance for you and your family • Flexible vacation policy • Generous parental leave • Growth Opportunities: Be part of a dynamic and growing team with numerous career development opportunities. • Inclusive Team: We value diversity and promote an inclusive culture where everyone can thrive. • Innovative Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking. • Hybrid & Remote Work: We embrace a mix of remote and hybrid work models depending on role and location, including our Chicago office, where some roles require regular in-office presence.